Stability analysis of stochastic recurrent neural networks with unbounded time-varying delays
โ Scribed by Xuejing Meng; Maosheng Tian; Shigeng Hu
- Publisher
- Elsevier Science
- Year
- 2011
- Tongue
- English
- Weight
- 225 KB
- Volume
- 74
- Category
- Article
- ISSN
- 0925-2312
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๐ SIMILAR VOLUMES
The stability of a class of stochastic Recurrent Neural Networks with time-varying delays is investigated in this paper. With the help of the Lyapunov function and the Dini derivative of the expectation of V (t, X (t)) ''along'' the solution X (t) of the model, a set of novel sufficient conditions o
In this paper, the global asymptotic stability is investigated for a class of neutral stochastic neural networks with time-varying delays and norm-bounded uncertainties. Based on Lyapunov stability theory and stochastic analysis approaches, delay-dependent criteria are derived to ensure the global,
Time-varying delays a b s t r a c t Because to apply a deterministic RNN to a noisy time series and the existence of a linear approximation are doubtful, we reconsider the solubility and stability of a recurrent neural network (RNN). Simpler methods are proposed to replace the complicated nonsingula